Investigation of the Radiographer's adherence and compliance with radiation protection and infection control practices during COVID-19 mobile radiography.

Radiological staff, especially radiographers, work as front liners against the COVID-19 outbreak. This study aims to assess compliance with radiation protection and infection control practices during COVID-19 mobile radiography procedures. This cross-sectional study included 234 radiographers (females, 56%, n = 131; males, 44%, n = 103) who were asked to complete an online questionnaire consisting of demographic data, radiation protection and infection control practices during COVID-19 portable cases, and knowledge and awareness. After informed consent was completed, SPSS statistical software was used for the data analysis. The most common age group of participants ranged from 18 to 25 years old (30.3%, n = 71). Bachelor's degree holders were 74.4% (n = 174). Most radiographers (39.7%, n = 93) had a working experience of 1-5 years, followed by 27.8% (n = 65) with more than 16 years of experience. Most respondents (62.4%, n = 146) handled approximately 1-5 cases daily, the majority of them (56%, n = 131) stated affirmatively they had obtained special training to handle COVID-19, and when inquired if they had received any special allowances for handling COVID-19 suspected/confirmed cases most of them stated negative (73.9%, n = 173). Most participants stated that they always wear a TLD during portable cases (67.1%, n = 157) and a lead apron (51.7%, n = 121). Around 73% (n = 171) knew the latest information on COVID-19 and attended the COVID-19 awareness course. A significant association was found between the work experience of the radiographers and their responses to following the best practices (p = 0.018, α = 0.05). Radiographers who had COVID-19 training (µ = 48.78) tend to adhere more to best practices than those who have not (p = 0.04, α = 0.05). Further, respondents who handled more than 16/more COVID-19 suspected/confirmed cases followed the best practices more (µ = 50.38) than those who handled less (p = 0.04, α = 0.05). This study revealed detailed information on radiation protection and infection control practices during COVID-19 mobile radiography. It has been observed that the participants/radiographers have good knowledge and awareness of radiation protection and infection-control practices. The present results may be used to plan future requirements regarding resources and training to ensure patient safety.

Risk factor analysis for inaccurate pre-operative MRI staging in rectal cancer.

BACKGROUND: Various tumor characteristics might lead to inaccurate local MRI-defined stage of rectal cancer and the purpose of this study was to explore the clinicopathological factors that impact on the precision pre-treatment MRI-defined stage of rectal cancer. METHODS: A retrospectively analysis was conducted in non-metastatic rectal cancer patients who received radical tumor resection without neoadjuvant treatment during 2007-2015 in the Sixth Affiliated Hospital of Sun Yat-sen University. Clinical T stage and N stage defined by pelvic enhanced MRI and pathological stage were compared and patients were subdivided into accurate-staging, over-staging and under-staging subgroups. Logistic regressions were used to explore risk factors for over-staging or under-staging. RESULTS: Five hundred fifty-one cases of patients were collected. Among them, 109 cases (19.4%) of patients were over-T-staged and 50 cases (8.9%) were under-T-staged, while 78 cases (13.9%) were over-N-staged and 75 cases (13.3%) were under-N-staged. Logistic regression suggested that pre-operative bowel obstruction was risk factor for over-T-staging (OR = 3.120, 95%CI: 1.662-5.857, P < 0.001) as well as over-N-staging (OR = 3.494, 95%CI: 1.797-6.794, P < 0.001), while mucinous adenocarcinoma was a risk factor for under-N-staging (OR = 4.049, 95%CI: 1.876-8.772, P < 0.001). Patients with larger tumor size were at lower risk for over-T-staging (OR = 0.837, 95%CI: 0.717-0.976, P = 0.024) and higher risk for over-N-staging (OR = 1.434, 95%CI: 1.223-1.680, P < 0.001). CONCLUSION: Bowel obstruction, mucinous adenocarcinoma and tumor size might have impact on the pre-operative MRI T staging or N staging of rectal cancer. Our results reminded clinicians to assess clinical stage individually in such rectal cancer patients.

A linear delay algorithm for enumerating all connected induced subgraphs.

BACKGROUND: Real biological and social data is increasingly being represented as graphs. Pattern-mining-based graph learning and analysis techniques report meaningful biological subnetworks that elucidate important interactions among entities. At the backbone of these algorithms is the enumeration of pattern space. RESULTS: We propose an efficient algorithm for enumerating all connected induced subgraphs of an undirected graph. Building on this enumeration approach, we propose an algorithm for mining all maximal cohesive subgraphs that integrates vertices' attributes with subgraph enumeration. To efficiently mine all maximal cohesive subgraphs, we propose two pruning techniques that remove futile search nodes in the enumeration tree. CONCLUSIONS: Experiments on synthetic and real graphs show the effectiveness of the proposed algorithm and the pruning techniques. On enumerating all connected induced subgraphs, our algorithm is several times faster than existing approaches. On dense graphs, the proposed approach is at least an order of magnitude faster than the best existing algorithm. Experiments on protein-protein interaction network with cancer gene dysregulation profile show that the reported cohesive subnetworks are biologically interesting.

Intrinsically disordered regions in autophagy proteins.

Autophagy is an essential eukaryotic pathway required for cellular homeostasis. Numerous key autophagy effectors and regulators have been identified, but the mechanism by which they carry out their function in autophagy is not fully understood. Our rigorous bioinformatic analysis shows that the majority of key human autophagy proteins include intrinsically disordered regions (IDRs), which are sequences lacking stable secondary and tertiary structure; suggesting that IDRs play an important, yet hitherto uninvestigated, role in autophagy. Available crystal structures corroborate the absence of structure in some of these predicted IDRs. Regions of orthologs equivalent to the IDRs predicted in the human autophagy proteins are poorly conserved, indicating that these regions may have diverse functions in different homologs. We also show that IDRs predicted in human proteins contain several regions predicted to facilitate protein-protein interactions, and delineate the network of proteins that interact with each predicted IDR-containing autophagy protein, suggesting that many of these interactions may involve IDRs. Lastly, we experimentally show that a BCL2 homology 3 domain (BH3D), within the key autophagy effector BECN1 is an IDR. This BH3D undergoes a dramatic conformational change from coil to α-helix upon binding to BCL2s, with the C-terminal half of this BH3D constituting a binding motif, which serves to anchor the interaction of the BH3D to BCL2s. The information presented here will help inform future in-depth investigations of the biological role and mechanism of IDRs in autophagy proteins.

Pyroptosis-related gene signature for predicting gastric cancer prognosis.

Gastric cancer (GC) is a prevalent form of malignancy characterized by significant heterogeneity. The development of a specific prediction model is of utmost importance to improve therapy alternatives. The presence of H. pylori can elicit pyroptosis, a notable carcinogenic process. Furthermore, the administration of chemotherapeutic drugs is often employed as a therapeutic approach to addressing this condition. In the present investigation, it was observed that there were variations in the production of 17 pyroptosis-regulating proteins between stomach tissue with tumor development and GC cells. The predictive relevance of each gene associated with pyroptosis was assessed using the cohort from the cancer genome atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) was utilized to enhance the outcomes of the regression approach. Patients with gastric cancer GC in the cohort from the TCGA were categorized into low-risk or high-risk groups based on their gene expression profiles. Patients with a low risk of gastric cancer had a higher likelihood of survival compared to persons classified as high risk (P<0.0001). A subset of patients diagnosed with GC from a Genes Expression Omnibus (GEO) cohort was stratified according to their overall survival (OS) duration. The statistical analysis revealed a higher significance level (P=0.0063) regarding OS time among low-risk individuals. The study revealed that the GC risk score emerged as a significant independent prognostic factor for OS in patients diagnosed with GC. The results of Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) research revealed that genes associated with a high-risk group had significantly elevated levels of immune system-related activity. Furthermore, it was found that the state of immunity was diminished within this particular group. The relationship between the immune response to cancer and pyroptosis genes is highly interconnected, suggesting that these genes have the potential to serve as prognostic indicators for GC.

Photoacoustic imaging in prostate cancer: A new paradigm for diagnosis and management.

The global health issue of prostate cancer (PCa) requires better diagnosis and treatment. Photoacoustic imaging (PAI) may change PCa management. This review examines PAI's principles, diagnostic role, and therapeutic guidance. PAI uses optical light excitation and ultrasonic detection for high-resolution functional and molecular imaging. PAI uses endogenous and exogenous contrast agents to distinguish cancerous and benign prostate tissues with greater sensitivity and specificity than PSA testing and TRUS-guided biopsy. In addition to diagnosing, PAI can guide and monitor PCa therapy. Its real-time imaging allows precise biopsies and brachytherapy seed placement. Photoacoustic temperature imaging allows non-invasive monitoring of thermal therapies like cryotherapy, improving treatment precision and success. Transurethral illumination probes, innovative contrast agents, integration with other imaging modalities, and machine learning analysis are being developed to overcome depth and data complexity restrictions. PAI could become an essential tool for PCa diagnosis and therapeutic guidance as the field advances.

Establishment of a local diagnostic reference level for computed tomography chest and abdomen in two different cities in Saudi Arabia.

BACKGROUND AND AIM: Spiral computed tomography (CT) scans, which are considered a high-contrast resolution, quick and cross-sectional imaging technique, have grown in popularity as a result of technological advancements. However, these advancements have brought with them the potential for significantly increased radiation doses to the patient. Consequently, many organizations recommended optimization and establishing diagnostic reference levels. The aim of the current study was to assess CT radiation dose and propose a local diagnostic reference level (LDRL) for the adult trunk [chest and abdomen] using CT dose parameters such as CT dose index volume (CTDIvol) and dose length product (DLP) as well as to compare the practices for aforementioned examinations between two hospitals in Taif and Abha cities in Saudi Arabia. MATERIALS AND METHODS: Data from 428 patients (216 for abdomen and 212 for chest) who were examined in two hospitals in Taif and Abha City in Saudi Arabia from December 2022 to March 2023, are used in this study. The data for hospitals in Taif and Abha are presented as 'T' and 'A' throughout this manuscript. The parameters of exposure and slice thickness were recorded in a specially designed data sheet together with the gender, age and patients morphometric. Microsoft Excel version 2010 was used to analyze results and plot the figures. The LDRL was achieved from the third quartile of CTDIvol and DLP for each hospital and examination. RESULTS: The average DLP (mGy-cm) and CTDIvol (mGy) for the chest and abdomen were 243 mGy cm, 5.8 mGy and 549 mGy cm, 8.6 mGy respectively. The average effective dose (ED) for chest and abdomen were 5.10 and 21.10 mSv, respectively. The proposed LDRL for the chest and abdomen were 6.9 mGy (CTDIvol), 375 mGy-cm (DLP), 7.8 mGy (CTDIvol), and 747 (DLP) mGy-cm, respectively. CONCLUSION: Hospital 'A' irradiated patients with a higher dose for the abdomen exam than Hospital 'T', but both hospitals agreed on the amount of radiation dose received by patients for chest imaging. The proposed LDRL for two examinations was less than the DRL obtained from the literature.

Psychological effect of COVID-19 pandemic on healthcare professionals of Yemen and coping strategies.

COVID-19 pandemic has triggered psychological stress such as anxiety and depression among people around the globe. Due to the nature of the job, healthcare professionals (HCPs) are at high risk of infection and are facing social stigma as well. This research was conducted with the objective to evaluate the psychological influence of the COVID-19 pandemic among HCPs in Yemen and the coping strategies adopted thereof. A web-based, as well as face-to-face cross-sectional study was carried out from July to December 2021 among HCPs of Yemen. The generalized anxiety disorder (GAD-7), patient health questionnaire (PHQ-9), and Brief-COPE scales were applied for the evaluation of anxiety, depression, and coping strategies. A total of 197 HCPs participated in the study where 28.4% and 43.1% had anxiety and depression respectively. The prevalence of both anxiety and depression in the majority were found of the minimal to none and mild categories (71.6% vs. 56.9% respectively). The respondents who had received training on COVID-19 had statistically significant lower GAD-7 scores than those who did not (6.32 vs. 8.02 respectively). A significant statistical difference was observed between physicians versus nurses regarding depression based on the working area (p < 0.05). The physician and pharmacist had a significant positive association with brief COPE scores at the 50th centile compared to other HCPs. The female respondents had statistically significant higher mean Brief COPE scores than male respondents (78.11 vs. 69.50 respectively). Our findings illustrate the requirement for efficient policies through administrative, clinical, and welfare perspectives from the regulatory body in preparedness and preventive measures towards such a pandemic that aids HCPs to provide service in a stress-free condition and assurance of a better healthcare system..

Geofold: topology-based protein unfolding pathways capture the effects of engineered disulfides on kinetic stability.

Protein unfolding is modeled as an ensemble of pathways, where each step in each pathway is the addition of one topologically possible conformational degree of freedom. Starting with a known protein structure, GeoFold hierarchically partitions (cuts) the native structure into substructures using revolute joints and translations. The energy of each cut and its activation barrier are calculated using buried solvent accessible surface area, side chain entropy, hydrogen bonding, buried cavities, and backbone degrees of freedom. A directed acyclic graph is constructed from the cuts, representing a network of simultaneous equilibria. Finite difference simulations on this graph simulate native unfolding pathways. Experimentally observed changes in the unfolding rates for disulfide mutants of barnase, T4 lysozyme, dihydrofolate reductase, and factor for inversion stimulation were qualitatively reproduced in these simulations. Detailed unfolding pathways for each case explain the effects of changes in the chain topology on the folding energy landscape. GeoFold is a useful tool for the inference of the effects of disulfide engineering on the energy landscape of protein unfolding.

Evaluation of Pediatric Imaging Modalities Practices of Radiologists and Technologists: A Survey-Based Study.

Introduction: Radiation protection for pediatric patients is the main concern in pediatric computed tomography (CT) due to their sensitive organs, such as the brain and the thyroid glands. Accordingly, an optimization of pediatric CT practices is vital to minimize the radiation dose for this population. Aim: To assess the pediatric CT practices of radiologists and technologists in a CT unit. Materials and Methods: The study was conducted among 26 hospitals, located in various regions in Saudi Arabia. A total of 200 hard copies of the questionnaire were distributed manually and were collected for analysis. In total, 117 completed surveys were gathered from technologies, while 49 were gathered from radiologists. Results: In the case of infants with hydrocephalus, 65% of the radiologists ordered an ultrasound (US), 24% ordered a head CT scan, and 10% ordered a magnetic resonance imaging (MRI) and general X-ray for diagnosis. For pediatric patients complaining of persistent headache, 59% and 27% of the radiologists recommended CT and MRI, respectively, for diagnosis. Conclusion: Most of the radiologists utilize CT head scan to diagnose persistent headache (by 59%) and ventriculoperitoneal shunt (VPS) malfunction (by 41%) in pediatric patients compared with the other modalities. The use of CT can increase the risk of later malignancy among pediatric patients due to radiation exposure. Alternative imaging modalities such as US and MRI (non-ionized radiation) should be considered to reduce the ionizing radiation hazards and optimize the current practices of radiologists. Most of the technologists follow radiation protection protocols in this study as 63% of the technologists used lead apron for pediatric patient's protection. Radiation awareness training for the technologists could improve the knowledge about the benefits of using lead apron and reduce the radiation risks in pediatric patients.

RASMA: a reverse search algorithm for mining maximal frequent subgraphs.

BACKGROUND: Given a collection of coexpression networks over a set of genes, identifying subnetworks that appear frequently is an important research problem known as mining frequent subgraphs. Maximal frequent subgraphs are a representative set of frequent subgraphs; A frequent subgraph is maximal if it does not have a super-graph that is frequent. In the bioinformatics discipline, methodologies for mining frequent and/or maximal frequent subgraphs can be used to discover interesting network motifs that elucidate complex interactions among genes, reflected through the edges of the frequent subnetworks. Further study of frequent coexpression subnetworks enhances the discovery of biological modules and biological signatures for gene expression and disease classification. RESULTS: We propose a reverse search algorithm, called RASMA, for mining frequent and maximal frequent subgraphs in a given collection of graphs. A key innovation in RASMA is a connected subgraph enumerator that uses a reverse-search strategy to enumerate connected subgraphs of an undirected graph. Using this enumeration strategy, RASMA obtains all maximal frequent subgraphs very efficiently. To overcome the computationally prohibitive task of enumerating all frequent subgraphs while mining for the maximal frequent subgraphs, RASMA employs several pruning strategies that substantially improve its overall runtime performance. Experimental results show that on large gene coexpression networks, the proposed algorithm efficiently mines biologically relevant maximal frequent subgraphs. CONCLUSION: Extracting recurrent gene coexpression subnetworks from multiple gene expression experiments enables the discovery of functional modules and subnetwork biomarkers. We have proposed a reverse search algorithm for mining maximal frequent subnetworks. Enrichment analysis of the extracted maximal frequent subnetworks reveals that subnetworks that are frequent are highly enriched with known biological ontologies.

Iterative non-sequential protein structural alignment.

Structural similarity between proteins gives us insights into their evolutionary relationships when there is low sequence similarity. In this paper, we present a novel approach called SNAP for non-sequential pair-wise structural alignment. Starting from an initial alignment, our approach iterates over a two-step process consisting of a superposition step and an alignment step, until convergence. We propose a novel greedy algorithm to construct both sequential and non-sequential alignments. The quality of SNAP alignments were assessed by comparing against the manually curated reference alignments in the challenging SISY and RIPC datasets. Moreover, when applied to a dataset of 4410 protein pairs selected from the CATH database, SNAP produced longer alignments with lower rmsd than several state-of-the-art alignment methods. Classification of folds using SNAP alignments was both highly sensitive and highly selective. The SNAP software along with the datasets are available online at http://www.cs.rpi.edu/~zaki/software/SNAP.

Information Loss Via Visual Assessment of Radiologic Images Using Modified Version of the Low-Contrast Detailed Phantom at Direct DR System.

INTRODUCTION: Quality in radiology images can be assessed by determining the levels of information retained or lost in an image. Information loss in images has been recently assessed via a method based on information theory and the employment of a contrast-detail (CD) phantom. In this study, the traditional CD phantom (air-Perspex) and a modified CD phantom were used. METHODS: Using the Agfa DX-D 600 digital flat panel system, six phantom radiographs were acquired at 70 kVp and 20 mAs. Three x-ray images were acquired for each phantom. RESULTS: Our results demonstrate that the material within the CD phantom influences total information loss (TIL) and image quality figure (IQF) measurements. The modified CD phantom provides a more realistic account of TIL and IQF for soft tissue radiology imaging. CONCLUSION: It is recommended that a low inherent subject contrast phantom, such as this modified CD phantom, be added to the image quality assessment processes of radiology departments. In addition, use of both IQF and TIL to assess image quality will provide radiology departments with greater evidence on which to base decisions.

Low-Contrast Detail Phantom: Proof of Concept.

PURPOSE: To investigate the concept of filling the air gaps of the conventional contrast detail phantom (CDP) with various concentrations of contrast media, and to develop a variable level of attenuation-level differential phantoms that could be more appropriate for contrast measurements in some radiology cases. METHODS: Images were acquired using the digital radiography system of the traditional CDP (Perspex/air hole phantom) and the novel form of CDP where the air holes were replaced with attenuating material. In this study, two different attenuating materials were introduced, water and a 30% concentration of iodine-based contrast medium. Image quality was assessed using automated processing to calculate the image quality factor (IQF)inv. RESULTS AND DISCUSSION: Phantom studies indicate that lower contrast levels are obtained when CDP holes are filled with water and a 30% concentration of iodine contrast media than those observed for air/Perspex or traditional CDP. As an example, when a 5-mAs beam is used the IQFinv values are 5.32 in the case of air filling the holes; however, when these holes are filled with water under the same conditions, the value of the IQFinv drops to 2.55, and to 2.83 when 30% of contrast media is used. Other concentrations were also tested. These results indicate that it is possible to extend the contrast scale in these phantoms to include ranges that are more realistic for a patient's body than just air and tissue-equivalent material. CONCLUSIONS: These findings indicate that the proposed extension of the contrast scales allows smaller changes in contrast to be discerned. This is due to the small attenuation differences of the subject materials (e.g, 30% contrast liquid and wax) from the traditional form of CDP (material/air). This suggests that the low form of the CDP may have a useful role in assessing image quality in planar radiology as an evaluation tool to better represent low-subject contrast imaging requirements.

Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm.

Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century. Big data is not "lots of data" as a phenomena anymore; The big data paradigm is putting the spirit of the Maginot Line into lots of data. Big data overall is disconnecting researchers and science challenges. We propose No-Boundary Thinking (NBT), applying no-boundary thinking in problem defining to address science challenges.

A microRNA-1280/JAG2 network comprises a novel biological target in high-risk medulloblastoma.

Over-expression of PDGF receptors (PDGFRs) has been previously implicated in high-risk medulloblastoma (MB) pathogenesis. However, the exact biological functions of PDGFRα and PDGFRß signaling in MB biology remain poorly understood. Here, we report the subgroup specific expression of PDGFRα and PDGFRß and their associated biological pathways in MB tumors. c-MYC, a downstream target of PDGFRß but not PDGFRα, is involved in PDGFRß signaling associated with cell proliferation, cell death, and invasion. Concurrent inhibition of PDGFRß and c-MYC blocks MB cell proliferation and migration synergistically. Integrated analysis of miRNA and miRNA targets regulated by both PDGFRß and c-MYC reveals that increased expression of JAG2, a target of miR-1280, is associated with high metastatic dissemination at diagnosis and a poor outcome in MB patients. Our study may resolve the controversy on the role of PDGFRs in MB and unveils JAG2 as a key downstream effector of a PDGFRß-driven signaling cascade and a potential therapeutic target.

Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets.

BACKGROUND: Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. RESULTS: We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways.

Mining maximal cohesive induced subnetworks and patterns by integrating biological networks with gene profile data.

With the availability of vast amounts of protein-protein, protein-DNA interactions, and genome-wide mRNA expression data for several organisms, identifying biological complexes has emerged as a major task in systems biology. Most of the existing approaches for complex identification have focused on utilizing one source of data. Recent research has shown that systematic integration of gene profile data with interaction data yields significant patterns. In this paper, we introduce the problem of mining maximal cohesive subnetworks that satisfy user-defined constraints defined over the gene profiles of the reported subnetworks. Moreover, we introduce the problem of finding maximal cohesive patterns which are sets of cohesive genes. Experiments on Yeast and Human datasets show the effectiveness of the proposed approach by assessing the overlap of the discovered subnetworks with known biological complexes. Moreover, GO enrichment analysis shows that the discovered subnetworks are biologically significant.

No-boundary thinking in bioinformatics research.

Currently there are definitions from many agencies and research societies defining "bioinformatics" as deriving knowledge from computational analysis of large volumes of biological and biomedical data. Should this be the bioinformatics research focus? We will discuss this issue in this review article. We would like to promote the idea of supporting human-infrastructure (HI) with no-boundary thinking (NT) in bioinformatics (HINT).

FlexSnap: flexible non-sequential protein structure alignment.

BACKGROUND: Proteins have evolved subject to energetic selection pressure for stability and flexibility. Structural similarity between proteins that have gone through conformational changes can be captured effectively if flexibility is considered. Topologically unrelated proteins that preserve secondary structure packing interactions can be detected if both flexibility and Sequential permutations are considered. We propose the FlexSnap algorithm for flexible non-topological protein structural alignment. RESULTS: The effectiveness of FlexSnap is demonstrated by measuring the agreement of its alignments with manually curated non-sequential structural alignments. FlexSnap showed competitive results against state-of-the-art algorithms, like DALI, SARF2, MultiProt, FlexProt, and FATCAT. Moreover on the DynDom dataset, FlexSnap reported longer alignments with smaller rmsd. CONCLUSIONS: We have introduced FlexSnap, a greedy chaining algorithm that reports both sequential and non-sequential alignments and allows twists (hinges). We assessed the quality of the FlexSnap alignments by measuring its agreements with manually curated non-sequential alignments. On the FlexProt dataset, FlexSnap was competitive to state-of-the-art flexible alignment methods. Moreover, we demonstrated the benefits of introducing hinges by showing significant improvements in the alignments reported by FlexSnap for the structure pairs for which rigid alignment methods reported alignments with either low coverage or large rmsd. AVAILABILITY: An implementation of the FlexSnap algorithm will be made available online at http://www.cs.rpi.edu/~zaki/software/flexsnap.